Overview

Dataset statistics

Number of variables9
Number of observations100000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 MiB
Average record size in memory72.0 B

Variable types

Numeric9

Warnings

mom has unique values Unique
H has unique values Unique
kb has unique values Unique
T has unique values Unique
alpha has unique values Unique
epsilon has unique values Unique
c has unique values Unique
M has unique values Unique
target has unique values Unique

Reproduction

Analysis started2021-07-29 22:51:11.309357
Analysis finished2021-07-29 23:03:49.879172
Duration12 minutes and 38.57 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

mom
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.998314767
Minimum1.000007326
Maximum2.999964123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:49.975008image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000007326
5-th percentile1.101006539
Q11.499464079
median1.995703296
Q32.497403455
95-th percentile2.900007595
Maximum2.999964123
Range1.999956797
Interquartile range (IQR)0.9979393756

Descriptive statistics

Standard deviation0.5769775785
Coefficient of variation (CV)0.2887320797
Kurtosis-1.197068933
Mean1.998314767
Median Absolute Deviation (MAD)0.4990728732
Skewness0.006722413778
Sum199831.4767
Variance0.3329031261
MonotonicityNot monotonic
2021-07-29T23:03:50.182273image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0812956121
 
< 0.1%
1.8596056291
 
< 0.1%
2.9410682691
 
< 0.1%
2.9376224291
 
< 0.1%
1.4869405671
 
< 0.1%
1.9405671961
 
< 0.1%
2.2625602261
 
< 0.1%
1.7576477551
 
< 0.1%
2.0713460011
 
< 0.1%
2.8268836911
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000073261
< 0.1%
1.0000106851
< 0.1%
1.0000154561
< 0.1%
1.0000174061
< 0.1%
1.0000194611
< 0.1%
1.0000482491
< 0.1%
1.0001029261
< 0.1%
1.0001100191
< 0.1%
1.000111191
< 0.1%
1.0001113591
< 0.1%
ValueCountFrequency (%)
2.9999641231
< 0.1%
2.9999506891
< 0.1%
2.9999435631
< 0.1%
2.9999427081
< 0.1%
2.9999201991
< 0.1%
2.9999153371
< 0.1%
2.9998727961
< 0.1%
2.9998611841
< 0.1%
2.9998327541
< 0.1%
2.9998265941
< 0.1%

H
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.000277795
Minimum1.000006603
Maximum2.9999836
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:50.408295image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000006603
5-th percentile1.101208682
Q11.501387305
median2.000958697
Q32.501191273
95-th percentile2.8992482
Maximum2.9999836
Range1.999976997
Interquartile range (IQR)0.9998039676

Descriptive statistics

Standard deviation0.5769446984
Coefficient of variation (CV)0.2884322868
Kurtosis-1.199456071
Mean2.000277795
Median Absolute Deviation (MAD)0.4998289427
Skewness-0.002279445119
Sum200027.7795
Variance0.332865185
MonotonicityNot monotonic
2021-07-29T23:03:50.610219image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.4241266561
 
< 0.1%
2.3062747511
 
< 0.1%
1.2680701881
 
< 0.1%
2.7758102321
 
< 0.1%
2.6515637511
 
< 0.1%
1.6905990061
 
< 0.1%
2.3568536661
 
< 0.1%
2.0752377621
 
< 0.1%
2.4458801181
 
< 0.1%
1.6771720651
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000066031
< 0.1%
1.0000233521
< 0.1%
1.0000442251
< 0.1%
1.0000825571
< 0.1%
1.000136051
< 0.1%
1.0001426531
< 0.1%
1.0001459421
< 0.1%
1.0001633771
< 0.1%
1.0001830441
< 0.1%
1.0001934481
< 0.1%
ValueCountFrequency (%)
2.99998361
< 0.1%
2.9999770431
< 0.1%
2.9999400041
< 0.1%
2.9999231251
< 0.1%
2.9999088481
< 0.1%
2.9998760411
< 0.1%
2.9998226291
< 0.1%
2.9997814391
< 0.1%
2.9997457821
< 0.1%
2.9997043911
< 0.1%

kb
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.999664091
Minimum1.000006079
Maximum2.999973576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:50.814964image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000006079
5-th percentile1.097531127
Q11.497906507
median2.001051257
Q32.501083124
95-th percentile2.900726054
Maximum2.999973576
Range1.999967498
Interquartile range (IQR)1.003176617

Descriptive statistics

Standard deviation0.5780667973
Coefficient of variation (CV)0.2890819512
Kurtosis-1.201562493
Mean1.999664091
Median Absolute Deviation (MAD)0.5015158163
Skewness-0.003837531801
Sum199966.4091
Variance0.3341612222
MonotonicityNot monotonic
2021-07-29T23:03:51.130621image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.9023415821
 
< 0.1%
2.7188033421
 
< 0.1%
2.3584966181
 
< 0.1%
2.1565770911
 
< 0.1%
2.2231938311
 
< 0.1%
1.3619847511
 
< 0.1%
2.6017333481
 
< 0.1%
1.2170141081
 
< 0.1%
2.9963790471
 
< 0.1%
2.4867851981
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000060791
< 0.1%
1.0000115461
< 0.1%
1.0000161281
< 0.1%
1.0000260431
< 0.1%
1.000045641
< 0.1%
1.0000685991
< 0.1%
1.0000818371
< 0.1%
1.0001284661
< 0.1%
1.0001671711
< 0.1%
1.0001779851
< 0.1%
ValueCountFrequency (%)
2.9999735761
< 0.1%
2.9999284611
< 0.1%
2.9999081161
< 0.1%
2.9998943171
< 0.1%
2.9998506081
< 0.1%
2.9997809911
< 0.1%
2.9997568241
< 0.1%
2.999747521
< 0.1%
2.9997277151
< 0.1%
2.9997193131
< 0.1%

T
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.999451936
Minimum1.000018663
Maximum2.999995235
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:51.346138image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000018663
5-th percentile1.100649651
Q11.499230787
median1.998977037
Q32.500621899
95-th percentile2.899083054
Maximum2.999995235
Range1.999976572
Interquartile range (IQR)1.001391113

Descriptive statistics

Standard deviation0.5771326771
Coefficient of variation (CV)0.2886454367
Kurtosis-1.200633786
Mean1.999451936
Median Absolute Deviation (MAD)0.5008146359
Skewness0.001877858834
Sum199945.1936
Variance0.333082127
MonotonicityNot monotonic
2021-07-29T23:03:51.548729image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.7005804621
 
< 0.1%
1.9451952591
 
< 0.1%
1.4450836521
 
< 0.1%
2.1069245441
 
< 0.1%
1.361263771
 
< 0.1%
2.2083429931
 
< 0.1%
2.2332342031
 
< 0.1%
2.3036671141
 
< 0.1%
1.8950216081
 
< 0.1%
2.9205507981
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000186631
< 0.1%
1.0000390991
< 0.1%
1.0000500771
< 0.1%
1.0001376081
< 0.1%
1.0001772111
< 0.1%
1.0002102931
< 0.1%
1.0002120961
< 0.1%
1.0002133351
< 0.1%
1.0002208011
< 0.1%
1.0002559281
< 0.1%
ValueCountFrequency (%)
2.9999952351
< 0.1%
2.9999245431
< 0.1%
2.9999223521
< 0.1%
2.999892891
< 0.1%
2.9998889581
< 0.1%
2.9998858331
< 0.1%
2.9998699371
< 0.1%
2.9998466841
< 0.1%
2.9998462551
< 0.1%
2.9998139031
< 0.1%

alpha
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.00296784
Minimum1.000019169
Maximum2.999985175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:51.755059image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000019169
5-th percentile1.100726227
Q11.504414796
median2.003308665
Q32.504705093
95-th percentile2.899525538
Maximum2.999985175
Range1.999966006
Interquartile range (IQR)1.000290297

Descriptive statistics

Standard deviation0.5773800871
Coefficient of variation (CV)0.2882622854
Kurtosis-1.200452236
Mean2.00296784
Median Absolute Deviation (MAD)0.500126335
Skewness-0.005681174021
Sum200296.784
Variance0.333367765
MonotonicityNot monotonic
2021-07-29T23:03:51.947900image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.6976712591
 
< 0.1%
1.7035787741
 
< 0.1%
1.8149583761
 
< 0.1%
1.5618817661
 
< 0.1%
1.2042614381
 
< 0.1%
1.891227081
 
< 0.1%
1.7874031061
 
< 0.1%
1.3138011471
 
< 0.1%
1.4930287891
 
< 0.1%
2.0742598451
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000191691
< 0.1%
1.0001017581
< 0.1%
1.0001159461
< 0.1%
1.000127661
< 0.1%
1.0001385371
< 0.1%
1.0001417551
< 0.1%
1.0001489861
< 0.1%
1.000160091
< 0.1%
1.0001862481
< 0.1%
1.0002151311
< 0.1%
ValueCountFrequency (%)
2.9999851751
< 0.1%
2.9999848411
< 0.1%
2.9999602731
< 0.1%
2.9999399961
< 0.1%
2.9999220321
< 0.1%
2.9999185331
< 0.1%
2.9998838561
< 0.1%
2.999841481
< 0.1%
2.9998240911
< 0.1%
2.9997819921
< 0.1%

epsilon
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.001936592
Minimum1.000010914
Maximum2.999976647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:52.153479image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000010914
5-th percentile1.101982641
Q11.504755553
median2.003147515
Q32.500188116
95-th percentile2.900543503
Maximum2.999976647
Range1.999965733
Interquartile range (IQR)0.9954325633

Descriptive statistics

Standard deviation0.5770341133
Coefficient of variation (CV)0.288237957
Kurtosis-1.197050455
Mean2.001936592
Median Absolute Deviation (MAD)0.4975927564
Skewness-0.004307513427
Sum200193.6592
Variance0.3329683679
MonotonicityNot monotonic
2021-07-29T23:03:52.350570image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.6685507521
 
< 0.1%
1.3850619331
 
< 0.1%
1.9565707261
 
< 0.1%
1.429181591
 
< 0.1%
2.1897139891
 
< 0.1%
1.7929791561
 
< 0.1%
1.5061057371
 
< 0.1%
1.9322768041
 
< 0.1%
1.5265824791
 
< 0.1%
1.004000231
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000109141
< 0.1%
1.0000114581
< 0.1%
1.0000131011
< 0.1%
1.0000137511
< 0.1%
1.0000741511
< 0.1%
1.0001068821
< 0.1%
1.000128251
< 0.1%
1.0001412771
< 0.1%
1.0001581721
< 0.1%
1.0001655461
< 0.1%
ValueCountFrequency (%)
2.9999766471
< 0.1%
2.9999720751
< 0.1%
2.9998794221
< 0.1%
2.9998731991
< 0.1%
2.9998644261
< 0.1%
2.9998407391
< 0.1%
2.999801261
< 0.1%
2.9997860441
< 0.1%
2.9997777021
< 0.1%
2.9997643781
< 0.1%

c
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.000258854
Minimum1.000001234
Maximum2.999981122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:52.557110image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000001234
5-th percentile1.100214581
Q11.500595888
median2.00092198
Q32.500080624
95-th percentile2.899058941
Maximum2.999981122
Range1.999979888
Interquartile range (IQR)0.9994847367

Descriptive statistics

Standard deviation0.5775194219
Coefficient of variation (CV)0.2887223425
Kurtosis-1.201530232
Mean2.000258854
Median Absolute Deviation (MAD)0.499669616
Skewness-0.001205477926
Sum200025.8854
Variance0.3335286827
MonotonicityNot monotonic
2021-07-29T23:03:52.755339image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.5217427111
 
< 0.1%
2.1002119151
 
< 0.1%
1.8319639051
 
< 0.1%
2.6209270321
 
< 0.1%
2.3415741251
 
< 0.1%
1.9684366691
 
< 0.1%
1.1675890991
 
< 0.1%
1.4921517151
 
< 0.1%
1.0887509911
 
< 0.1%
1.3005859391
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000012341
< 0.1%
1.0000036341
< 0.1%
1.0000168671
< 0.1%
1.0000283941
< 0.1%
1.0000410161
< 0.1%
1.000093721
< 0.1%
1.0001471961
< 0.1%
1.0001630761
< 0.1%
1.0001657941
< 0.1%
1.000201751
< 0.1%
ValueCountFrequency (%)
2.9999811221
< 0.1%
2.9999776681
< 0.1%
2.9999709921
< 0.1%
2.9999371881
< 0.1%
2.999858471
< 0.1%
2.9998165851
< 0.1%
2.9998085221
< 0.1%
2.9997881611
< 0.1%
2.9997708371
< 0.1%
2.9997363291
< 0.1%

M
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.998606848
Minimum1.000007373
Maximum2.999972
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:52.969189image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000007373
5-th percentile1.099773944
Q11.50115999
median1.998992608
Q32.494884231
95-th percentile2.899180721
Maximum2.999972
Range1.999964627
Interquartile range (IQR)0.9937242411

Descriptive statistics

Standard deviation0.5758879137
Coefficient of variation (CV)0.2881446714
Kurtosis-1.191706292
Mean1.998606848
Median Absolute Deviation (MAD)0.4970066784
Skewness-0.001208492651
Sum199860.6848
Variance0.3316468891
MonotonicityNot monotonic
2021-07-29T23:03:53.167539image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.8079990161
 
< 0.1%
1.1376484441
 
< 0.1%
1.1643912581
 
< 0.1%
2.9671945181
 
< 0.1%
2.8229241371
 
< 0.1%
2.8448217831
 
< 0.1%
2.1395464211
 
< 0.1%
2.3256855161
 
< 0.1%
2.8485253911
 
< 0.1%
1.2171452381
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000073731
< 0.1%
1.0000310731
< 0.1%
1.0000395651
< 0.1%
1.0000419891
< 0.1%
1.0000927431
< 0.1%
1.000111161
< 0.1%
1.0001685941
< 0.1%
1.0001757581
< 0.1%
1.0001952621
< 0.1%
1.0001953421
< 0.1%
ValueCountFrequency (%)
2.9999721
< 0.1%
2.9999655141
< 0.1%
2.9999324391
< 0.1%
2.9999322471
< 0.1%
2.9999305641
< 0.1%
2.9999207131
< 0.1%
2.9999020651
< 0.1%
2.9999019341
< 0.1%
2.9998890351
< 0.1%
2.9998823711
< 0.1%

target
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.646811558
Minimum0.1428945512
Maximum16.33009472
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T23:03:53.377357image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.1428945512
5-th percentile0.4885406578
Q10.8848186908
median1.352321867
Q32.078812234
95-th percentile3.797308739
Maximum16.33009472
Range16.18720017
Interquartile range (IQR)1.193993543

Descriptive statistics

Standard deviation1.116606794
Coefficient of variation (CV)0.6780416307
Kurtosis7.473224842
Mean1.646811558
Median Absolute Deviation (MAD)0.549821188
Skewness2.076352646
Sum164681.1558
Variance1.246810733
MonotonicityNot monotonic
2021-07-29T23:03:53.675264image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.54828524671
 
< 0.1%
0.92249024861
 
< 0.1%
1.3719828561
 
< 0.1%
2.0998130491
 
< 0.1%
1.4419153411
 
< 0.1%
1.5904186381
 
< 0.1%
1.6430640881
 
< 0.1%
1.7462690371
 
< 0.1%
1.7495692151
 
< 0.1%
1.2314303731
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
0.14289455121
< 0.1%
0.1647402141
< 0.1%
0.17185615471
< 0.1%
0.18019107281
< 0.1%
0.18069606661
< 0.1%
0.18143356421
< 0.1%
0.18261809591
< 0.1%
0.18455008951
< 0.1%
0.18475169131
< 0.1%
0.18752287981
< 0.1%
ValueCountFrequency (%)
16.330094721
< 0.1%
15.786025941
< 0.1%
14.448288271
< 0.1%
13.83242651
< 0.1%
12.786978041
< 0.1%
12.082507221
< 0.1%
12.009621381
< 0.1%
11.910523041
< 0.1%
11.750758881
< 0.1%
11.731323251
< 0.1%

Interactions

2021-07-29T23:03:33.285935image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:33.480107image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:33.665489image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:33.849356image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:34.042569image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:34.230012image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:34.421429image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:34.614095image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:34.817137image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:35.001739image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:35.190462image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:35.382804image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:35.576509image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:35.765089image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:35.959073image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:36.156450image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:36.483879image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:36.673325image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:36.865358image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:37.054624image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:37.261909image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:37.460890image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:37.656584image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:37.855173image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:38.042782image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:38.233992image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:38.417858image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:38.601897image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:38.792551image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:38.981541image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:39.171749image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:39.359890image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:39.551909image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:39.750061image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:39.932981image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:40.238810image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:40.432677image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:40.620796image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:40.807754image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:40.992688image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:41.186355image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:41.380286image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:41.568745image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:41.751924image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:41.940328image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:42.122623image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:42.313902image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:42.501407image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:42.692281image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:42.887411image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:43.081587image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:43.274172image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:43.464532image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:43.659214image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:43.966458image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:44.151330image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:44.335015image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:44.520542image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:44.706295image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:44.891224image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:45.080990image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:45.273435image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:45.458522image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:45.653667image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:45.854032image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:46.042600image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:46.234393image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:46.428920image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:46.624371image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:46.813531image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:46.996266image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:47.190797image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:47.372039image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:47.665587image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:47.842449image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:48.026372image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:48.215668image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:48.401064image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:48.588210image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:48.769465image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T23:03:48.954751image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2021-07-29T23:03:53.853571image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-07-29T23:03:54.067763image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-07-29T23:03:54.277646image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-07-29T23:03:54.493011image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-07-29T23:03:49.254542image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-07-29T23:03:49.542282image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

momHkbTalphaepsiloncMtarget
01.0812962.4241271.9023422.7005801.6976712.6685512.5217431.8079990.548285
12.6206982.1013351.0797781.8989762.4601851.8979061.9803522.0119293.535639
22.4323991.8510762.6157762.6548741.6116342.2065192.4125311.3733490.708722
31.0093002.4627041.5103192.2051941.0511181.7723351.9370372.3840530.860502
42.6362812.6584752.5158581.9965592.4020212.7427232.5082191.0580641.472565
52.1477071.6850522.6002022.6330752.2381981.9929412.4747551.4550750.612290
62.6480332.5918031.9138132.3469772.8310061.0821251.5535622.7230913.268114
72.8287231.1448201.2143882.7846062.9715041.8949011.7212812.0681841.873331
81.3465072.7391452.6679032.7519822.8405941.6998472.3250872.2076030.627503
92.4453111.0552311.2927051.8813742.0525372.9675022.7856131.1100981.160469

Last rows

momHkbTalphaepsiloncMtarget
999901.9103131.7479881.1855802.6410212.4939501.6027891.4299211.2146171.630384
999912.4204082.7591071.6068221.7802741.7445281.4650772.4954112.1241012.678217
999922.1182282.4755281.0877311.4110392.6097882.8199281.3586211.3710534.365207
999932.5856332.1969942.4274691.5845752.9812931.8025772.5021022.8159151.976884
999941.4340121.9277001.8372752.3593901.6874351.1057141.8484632.7412151.042731
999951.2177562.2512472.9094581.9628091.4840601.7278792.6628191.0026860.505957
999962.1170371.9692171.1356542.2078782.9383571.9331262.4280452.8671592.286801
999972.8602861.8358751.5795511.0593061.4278571.3556092.9376922.1369513.584167
999981.8893881.9932892.0428112.8438071.3033911.9235491.3955142.4568490.926300
999992.9301002.4399321.0887152.7656662.4581702.1099901.5491322.9356543.761204